This paper applies the Cell Assemblies (CAs) model to Information Retrieval. CAs are reverberating circuits of neurons that can persist long beyond the initial stimulus has ceased. CAs are learned through Hebbian learning rules and have been used to simulate the formation and the usage of human concepts. We adapted the CAs model to learn relationships between the terms in a document collection. The method will be validated by means of experiments on standard IR test collections.